{"id":"W2614239652","doi":"10.5194/isprs-archives-xlii-5-w1-9-2017","title":"HARNESSING DIGITAL WORKFLOWS FOR CONSERVING HISTORIC PLACES","year":2017,"lang":"en","type":"article","venue":"The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences","topic":"Conservation Techniques and Studies","field":"Arts and Humanities","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Cornerstone; Documentation; Workflow; Work (physics); Resource (disambiguation); Public use; Historic site; Event (particle physics); Process (computing); Public access; Property (philosophy); History; Architectural engineering; Environmental resource management; Environmental planning; Engineering; Geography; Computer science; Political science; Archaeology; World Wide Web; Database; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0140147,0.001226278,0.000801828,0.005810873,0.002447593,0.00884086,0.00383185,0.001458926,0.006123614],"category_scores_gemma":[0.02749228,0.0009396381,0.001510853,0.004483634,0.002126113,0.01043306,0.01043152,0.002346506,0.00257376],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00155379,"about_ca_system_score_gemma":0.00443054,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008476301,"about_ca_topic_score_gemma":0.0132117,"domain_scores_codex":[0.9929214,0.002390308,0.001150217,0.0012902,0.001808992,0.0004388641],"domain_scores_gemma":[0.9717306,0.008142715,0.001939443,0.01234805,0.003475047,0.002364047],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006898433,0.0009385948,0.01540388,0.001049523,0.0001888594,0.001602085,0.01141365,0.0334722,0.008832663,0.1086088,0.0243465,0.7934534],"study_design_scores_gemma":[0.0002549105,0.0003590622,0.005426889,0.00143989,0.0002891978,0.0008763928,0.009192931,0.3072973,0.02077844,0.3180082,0.3357143,0.0003624282],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03547419,0.0005803531,0.9151312,0.002443341,0.0003183086,0.001078944,0.001425471,0.02595106,0.0175972],"genre_scores_gemma":[0.1999383,0.0007301051,0.7871541,0.0003436873,0.00009005866,0.0006460713,0.003415121,0.001552029,0.006130557],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0140147,"threshold_uncertainty_score":0.07411766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03582715352016537,"score_gpt":0.267334279483065,"score_spread":0.2315071259628996,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}